{
 "cells": [
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:35:07.941297Z",
     "start_time": "2025-06-10T05:35:07.935400Z"
    }
   },
   "source": [
    "import numpy as np \n",
    "import math \n",
    "import pandas as pd \n",
    "pd.set_option('display.float_format',lambda x:'%.3f' % x)\n",
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('ggplot')\n",
    "%matplotlib inline\n",
    "import seaborn as sns \n",
    "sns.set_palette('muted')\n",
    "sns.set_style('darkgrid')\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import os \n",
    "os.chdir('F:/安装包/PPD-First-Round-Data-Updated/PPD-First-Round-Data-Update/')\n",
    "import lightgbm as lgb \n",
    "from lightgbm import plot_importance"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:35:16.202690Z",
     "start_time": "2025-06-10T05:35:13.914536Z"
    }
   },
   "source": [
    "# 导入feature_processing处理过后的数据\n",
    "data = pd.read_csv('data1_process.csv',encoding='gb18030')\n",
    "periods_df = pd.read_csv('periods_feature.csv',encoding='gbk')\n",
    "rank_df = pd.read_csv('rank_feature.csv',encoding='gbk')\n",
    "update_info = pd.read_csv('update_feature.csv',encoding='gbk')\n",
    "log_df = pd.read_csv('log_info_feature.csv',encoding='gbk')"
   ],
   "outputs": [],
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:35:18.314927Z",
     "start_time": "2025-06-10T05:35:18.201398Z"
    }
   },
   "source": [
    "# 合并衍生后的变量，data1不包含排序特征和periods衍生特征\n",
    "data1 = pd.merge(data,update_info,on='Idx',how='left')\n",
    "data1 = pd.merge(data1,log_df,on='Idx',how='left')\n",
    "data1.shape"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(49701, 237)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "metadata": {
    "scrolled": true,
    "ExecuteTime": {
     "end_time": "2025-06-10T05:35:20.112470Z",
     "start_time": "2025-06-10T05:35:20.043834Z"
    }
   },
   "source": [
    "# data2包含排序特征和periods衍生特征\n",
    "data2 = pd.concat([data1,rank_df,periods_df],axis=1)\n",
    "data2.shape"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(49701, 423)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:39:56.921449Z",
     "start_time": "2025-06-10T05:39:30.189746Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import lightgbm as lgb\n",
    "from lightgbm import early_stopping, log_evaluation\n",
    "\n",
    "# 假设 data 和 data1 已经加载\n",
    "data_idx = data.Idx\n",
    "df1 = data1.drop(['Idx'], axis=1)  # 删除Idx\n",
    "\n",
    "# 测试集训练集的划分\n",
    "train_fea = np.array(df1[df1['target'].notnull()][df1.sample_status == 'train'].drop(['sample_status', 'target'], axis=1))\n",
    "test_fea = np.array(df1[df1.sample_status == 'test'].drop(['sample_status', 'target'], axis=1))\n",
    "train_label = np.array(df1[df1['target'].notnull()][df1.sample_status == 'train']['target']).reshape(-1, 1)\n",
    "test_label = np.array(df1[df1.sample_status == 'test']['target']).reshape(-1, 1)\n",
    "\n",
    "fea_names = list(df1.drop(['sample_status', 'target'], axis=1).columns)  # 特征名字存成列表\n",
    "feature_importance_values = np.zeros(len(fea_names))  # 初始化特征重要性数组\n",
    "\n",
    "# 训练10个lightgbm，并对10个模型输出的feature_importances_取平均\n",
    "for _ in range(10):\n",
    "    # 初始化模型时设置verbose参数\n",
    "    model = lgb.LGBMClassifier(\n",
    "        n_estimators=400,\n",
    "        learning_rate=0.05,\n",
    "        n_jobs=-1,\n",
    "        verbose=-1  # 控制初始化和训练过程中的日志级别\n",
    "    )\n",
    "\n",
    "    # 不使用验证集的训练方式\n",
    "    model.fit(\n",
    "        train_fea,\n",
    "        train_label,\n",
    "        eval_metric='auc'\n",
    "    )\n",
    "\n",
    "    # 或者使用验证集和早停（取消下面注释并注释上面的fit()调用）\n",
    "    # model.fit(\n",
    "    #     train_fea,\n",
    "    #     train_label,\n",
    "    #     eval_metric='auc',\n",
    "    #     eval_set=[(test_fea, test_label)],\n",
    "    #     early_stopping_rounds=100,\n",
    "    #     callbacks=[log_evaluation(30)]  # 每30轮打印一次评估结果\n",
    "    # )\n",
    "\n",
    "    feature_importance_values += model.feature_importances_ / 10\n",
    "\n",
    "# 将feature_importance_values存成临时表\n",
    "fea_imp_df1 = pd.DataFrame({\n",
    "    'feature': fea_names,\n",
    "    'fea_importance': feature_importance_values\n",
    "})\n",
    "fea_imp_df1 = fea_imp_df1.sort_values('fea_importance', ascending=False).reset_index(drop=True)\n",
    "fea_imp_df1['norm_importance'] = fea_imp_df1['fea_importance'] / fea_imp_df1['fea_importance'].sum()  # 特征重要性归一化\n",
    "fea_imp_df1['cum_importance'] = np.cumsum(fea_imp_df1['norm_importance'])  # 特征重要性累加值\n",
    "\n",
    "print(fea_imp_df1.head())"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      feature  fea_importance  norm_importance  cum_importance\n",
      "0            avg_log_timespan         203.000            0.017           0.017\n",
      "1   ThirdParty_Info_Period2_5         164.000            0.014           0.031\n",
      "2                 UserInfo_18         162.000            0.013           0.044\n",
      "3  ThirdParty_Info_Period4_15         154.000            0.013           0.057\n",
      "4   ThirdParty_Info_Period4_5         152.000            0.013           0.070\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:40:06.747516Z",
     "start_time": "2025-06-10T05:40:06.204506Z"
    }
   },
   "source": [
    "# 特征重要性可视化\n",
    "plt.figure(figsize=(16,5))\n",
    "plt.rcParams['font.sans-serif']=['Microsoft YaHei']\n",
    "plt.subplot(1,2,1)\n",
    "plt.title('特征重要性')\n",
    "sns.barplot(data=fea_imp_df1.iloc[:10,:],x='norm_importance',y='feature')\n",
    "plt.subplot(1,2,2)\n",
    "plt.title('特征重要性累加图')\n",
    "plt.xlabel('特征个数')\n",
    "plt.ylabel('cum_importance')\n",
    "plt.plot(list(range(1, len(fea_names)+1)),fea_imp_df1['cum_importance'], 'r-')\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x500 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:40:10.116640Z",
     "start_time": "2025-06-10T05:40:10.109061Z"
    }
   },
   "source": [
    "# 剔除特征重要性为0的变量\n",
    "zero_imp_col = list(fea_imp_df1[fea_imp_df1.fea_importance==0].feature)\n",
    "fea_imp_df11 = fea_imp_df1[~(fea_imp_df1.feature.isin(zero_imp_col))]\n",
    "print('特征重要性为0的变量个数为 ：{}'.format(len(zero_imp_col)))\n",
    "print(zero_imp_col)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特征重要性为0的变量个数为 ：36\n",
      "['_creationdate', '_secondmobile', '_secondemail', '_ppdaiaccount', '_otherwebshoptype', '_contactid', '_hassborgjj', '_orderid', '_userid', '_position', '_bussinessaddress', '_hasbusinesslicense', '_hasppdaiaccount', '_phonetype', 'is_weifang_UserInfo20', '_idaddress', '_byuserid', 'is_zibo_UserInfo8', 'WeblogInfo_19_E', 'WeblogInfo_19_G', 'WeblogInfo_19_H', 'WeblogInfo_19_J', '_relationshipid', '_age', '_gender', '_flag_uctopvr', '_graduateschool', '_companytypeid', '_companysizeid', '_nickname', '_webshoptypeid', '_webshopurl', '_dormitoryphone', '_schoolname', '_graduatedate', 'is_weifang_UserInfo4']\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:40:12.460484Z",
     "start_time": "2025-06-10T05:40:12.455148Z"
    }
   },
   "source": [
    "# 剔除特征重要性比较弱的变量\n",
    "low_imp_col = list(fea_imp_df11[fea_imp_df11.cum_importance>=0.99].feature)\n",
    "print('特征重要性比较弱的变量个数为：{}'.format(len(low_imp_col)))\n",
    "print(low_imp_col)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特征重要性比较弱的变量个数为：36\n",
      "['WeblogInfo_21_A', '_companyphone', 'is_zibo_UserInfo2', 'is_heilongj_userinfo19', 'is_jilin_userinfo19', '_districtid', '_cityid', 'WeblogInfo_36', 'WeblogInfo_21_B', '_iscash', 'is_tianjin_userinfo7', '_regstepid', '_marriagestatusid', 'is_zibo_UserInfo20', '_residencephone', '_provinceid', '_flag_uctobcp', '_phone', 'WeblogInfo_24', 'is_chengdu_UserInfo4', 'WeblogInfo_19_I', '_hasbuycar', '_companyname', 'is_chengdu_UserInfo20', 'WeblogInfo_21_D', 'is_yantai_UserInfo2', 'is_sichuan_userinfo7', 'is_jilin_userinfo7', '_residenceyears', '_educationid', '_workyears', 'WeblogInfo_21_C', '_residenceaddress', 'SocialNetwork_17', 'is_sichuan_userinfo19', '_residencetypeid']\n"
     ]
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:40:14.070953Z",
     "start_time": "2025-06-10T05:40:14.049192Z"
    }
   },
   "source": [
    "# 删除特征重要性为0和比较弱的特征\n",
    "drop_imp_col = zero_imp_col+low_imp_col\n",
    "mydf1 = df1.drop(drop_imp_col,axis=1)\n",
    "mydf1.shape"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(49701, 164)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 11
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-10T05:40:19.236739Z",
     "start_time": "2025-06-10T05:40:15.398418Z"
    }
   },
   "source": [
    "# 加上训练集测试集状态，保存数据\n",
    "sample_status = list(df1.sample_status)\n",
    "mydf1['sample_status'] = sample_status\n",
    "mydf1['Idx'] = data_idx\n",
    "mydf1.to_csv('./feature_select_data1.csv',encoding='gb18030',index=False)"
   ],
   "outputs": [],
   "execution_count": 12
  }
 ],
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